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FASAL VYAPAR

FASAL VYAPAR

Ek hi jagah sabke liye!

Created on 23rd February 2025

FASAL VYAPAR

FASAL VYAPAR

Ek hi jagah sabke liye!

The problem FASAL VYAPAR solves

Farmers struggle with crop disease, soil quality analysis, crops condition an selling the produce at fair prices. So, we have come with an idea that we will eliminate all the middle men between the farmers and the shopkeepers then we have also identified that there is a major problem in the inventory system of the farmers, so we have come up with a AI model which will first identify the crops that the farmers will take a photo or pick up from the galary of their mobile app and it will show automatically the condition of the crops and we give the option to the farmers that they can direct upload the crops to their inventory. After that we are also making shopkeeper window where the shopkeeper can access the crops listed by the farmers with their expiry date and it will show the product that are divided into the various condition the crops current situation is, their is also a inventory system same like a farmer where shopkeeper can also analysis the inventory and then sell to the users. And in the user section they is three options first is calories detections which is run by fruit detection model and its shows the calories and it has also a market place for buying products directly from the shopkeepers. So our main AIM is first to help the farmers from the basic (soil detection for their crops) to advanced (automatic inventory management system) and to eliminate all the middle man that we have seen that it will increase the profit of about 50% and feasibility to our own farmers. And for the shopkeepers the major help that like amazon he can choose which product he have to buy at what point of time and to sell. Then for the user part the feasibilities are that nowadays we have seen many GYM freaks who are determind about the calories intake so in our app he/she can order best on the calories he/she needed that day.

A details work flow is attached below.

Challenges we ran into

  1. we face multiple issue to train our model into our laptops because our laptops gpus are lesser performance and small vrams

Tracks Applied (1)

MongoDB

1.Flexible schema Real time data store for AI Scalable and high performance. Security and Backup
Major League Hacking

Major League Hacking

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